A novel feature extraction scheme for face recognition

Security and authentication of a person is a crucial part of any industry. There are many techniques used for this purpose. One of them is face recognition. Face recognition is an effective means of authenticating a person. The advantage of this approach is that, it enables us to detect changes in the face pattern of an individual to an appreciable extent. The recognition system can tolerate local variations in the face expression of an individual. Hence face recognition can be used as a key factor in crime detection mainly to identify criminals. There are several approaches to face recognition of which Principal Component Analysis (PCA) and Gabor Wavelet Transform (GWT) have been incorporated in this paper. The system consists of a database of a set of facial patterns for each individual. The characteristic features called `EigenFaces´ are extracted from the stored images using which the system is trained for subsequent recognition of new images..